I am a Research Scientist at LG AI Research. I received my PhD from the Computer Science Department at the University of Michigan, where I worked on topics including representation learning, learning from limited supervision and language grounding. More recently, I have been interested in enhancing the planning, reasoning and agent capabilities of language models.

Talks

Selected Publications

  • Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents.
    Yunseok Jang*, Yeda Song*, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Dong-Ki Kim, Kyunghoon Bae, Honglak Lee.
    CVPR 2025

  • Autoguide: Automated generation and selection of state-aware guidelines for large language model agents. [paper]
    Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee.
    NeurIPS 2024

  • Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents [paper]
    Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
    EMNLP Findings 2024

  • Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense [paper]
    Siqi Shen, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Soujanya Poria, Rada Mihalcea
    NAACL 2024 (Social Impact Award)

  • Code Models are Zero-shot Precondition Reasoners [paper]
    Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu, Anthony Zhe Liu, Dong-Ki Kim, Dongsub Shim, Moontae Lee, Honglak Lee
    NAACL 2024 (Also at Neurips FMDM Workshop 2023)

  • Unsupervised Task Graph Generation from Instructional Video Transcripts [paper]
    Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee
    Findings of ACL 2023 (Also at ACL WNU Workshop 2023)

  • Knowledge Unlearning for Mitigating Privacy Risks in Language Models [paper]
    Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, Minjoon Seo
    ACL 2023

  • Exploring the Benefits of Training Expert Language Models over Instruction Tuning [paper]
    Joel Jang, Seungone Kim, Seonghyeon Ye, Doyoung Kim, Lajanugen Logeswaran, Moontae Lee, Kyungjae Lee, Minjoon Seo
    ICML 2023

  • Few-shot Subgoal Planning with Language Models [paper]
    Lajanugen Logeswaran, Violet Fu, Moontae Lee, Honglak Lee
    NAACL 2022 (Also at ACL CSRR workshop 2022)

  • Zero-Shot Entity Linking by Reading Entity Descriptions [paper]
    Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee
    ACL 2019 (Nominated for best paper)

  • Content Preserving Text Generation with Attribute Controls [paper]
    Lajanugen Logeswaran, Honglak Lee, Samy Bengio
    NIPS 2018

  • An Efficient Framework for Learning Sentence Representations [paper]
    Lajanugen Logeswaran, Honglak Lee
    ICLR 2018

Professional Experience

  • Research Scientist, LG AI Research (Ann Arbor), Jul 2021 - Present
  • Research Intern, Facebook AI Research (New York), May - Aug 2019
  • Research Intern, Google Research (Seattle), May 2018 - Jan 2019
  • Research Intern, Google Brain (Mountain View), Feb - Jun 2017

Awards & Honors

  • IEEEXtreme 24 hour Programming Competition - 24th place (2013)
  • INexus International Robot Competition - 3rd place (2012)
  • Bronze medal at the 50th International Mathematical Olympiad (2009)
  • Gold medal at Sri Lankan Mathematics Olympiad (2007)